Targeted metagenomics (metabarcoding) enables the identification of organisms (bacteria, archaea, eukaryotes) present in complex environments (tissues, faeces, saliva, soil samples, water, air, food, etc.). This method, which is an alternative to culturing samples in the laboratory, is based on the analysis of environmental DNA using next-generation sequencing (NGS) of targeted DNA regions, which have been previously amplified by PCR.
Metabarcoding analysis using next-generation sequencing (NGS) involves several steps. First, total DNA is extracted from the sample, after which a taxonomically informative marker common to a specific group of interest is amplified. It is also possible to analyse several markers of interest simultaneously using multiplexing. The resulting amplicons are sequenced and analysed using bioinformatics to determine which organisms are present in the sample and their relative abundance.
PGTB offers this analysis as short-read sequencing on Illumina’s MiSeq i100 and NextSeq 2000 sequencers, and as long-read sequencing on Oxford Nanopore Technologies’ PromethION 2 Solo sequencer:
| Short read | Long read | |
| Maximum number of sequences per run | 300 M (2×300 pb) | 5 M |
| Maximum number of samples per run | 1140 | 96 |
IMPORTANT : For targeted metagenomic analyses, Illumina recommends using 35% PhiX to avoid compromising the quality of the data produced due to the lack of diversity in this type of library. We follow these recommendations, which results in a proportional reduction in the number of usable reads.
The PGTB also provides a dedicated DNA laboratory for the extraction of DNA from environmental samples and the preparation of libraries under optimal conditions.
- Targeted metagenomics using an Illumina sequencer
Services
Number of samples: 95 to 1,140 per run. One well per plate is left empty for the PGTB internal control.
Sample type: DNA or PCR products with a specific molecular tail
Sequencing on the Illumina MiSeq i100 or NextSeq 2000: selecting the flow cell based on the number of samples and targets analysed, and the target sequencing depth.
Requirements
Requirements for metabarcoding from DNA
Requirements for metabarcoding from PCR1 products
Results
Sent by email or uploaded to a server
Depending on the service requested:
- Demultiplexed FASTQ files
- Sequencing run report (MultiQC)
- If bioanalysis: report and file containing the results of the data analysis (table showing the abundance of OTUs or ASVs along with their taxonomic assignments, etc.)
- Targeted metagenomics on the P2 Solo sequencer
Services
Number of samples: to be determined based on the size of the targets
Sample type: DNA or PCR products with a specific molecular tail
Requirements
Sufficient DNA integrity and purity to obtain long-range PCR products
Intégrité et pureté des ADN suffisants pour obtenir des produits de PCR long range
Results
Sent by email or uploaded to a server
Depending on the service requested:
- Demultiplexed FASTQ files
- Sequencing run report (PycoQC)
- Analysis on the EPI2ME platform (16S, WIMP...).
Associated publications
Barroso-Bergadà, D., Delmotte, F., Faivre d’Arcier, J., Massot, M., Chancerel, E., Demeaux, I., Guimier, S., Guichoux, E., Bohan, D.A., Vacher, C., 2023a. Leaf Microbiome Data for European Cultivated Grapevine ( Vitis vinifera ) During Downy Mildew ( Plasmopara viticola ) Epidemics in Three Wine-Producing Regions in France. PhytoFrontiers™ 3, 477–483. https://doi.org/10.1094/PHYTOFR-11-22-0138-A
Barroso-Bergadà, D., Massot, M., Vignolles, N., Faivre d’Arcier, J., Chancerel, E., Guichoux, E., Walker, A.-S., Vacher, C., Bohan, D.A., Laval, V., Suffert, F., 2023b. Metagenomic Next-Generation Sequencing (mNGS) Data Reveal the Phyllosphere Microbiome of Wheat Plants Infected by the Fungal Pathogen Zymoseptoria tritici. Phytobiomes Journal 7, 281–287. https://doi.org/10.1094/PBIOMES-02-22-0008-FI
Cambon, M.C., Cartry, D., Chancerel, E., Ziegler, C., Levionnois, S., Coste, S., Stahl, C., Delzon, S., Buée, M., Burban, B., Cazal, J., Fort, T., Goret, J.-Y., Heuret, P., Léger, P., Louisanna, E., Ritter, Y., Bonal, D., Roy, M., Schimann, H., Vacher, C., 2023a. Drought Tolerance Traits in Neotropical Trees Correlate with the Composition of Phyllosphere Fungal Communities. Phytobiomes Journal 7, 244–258. https://doi.org/10.1094/PBIOMES-04-22-0023-R
Cambon, M.C., Trillat, M., Lesur‐Kupin, I., Burlett, R., Chancerel, E., Guichoux, E., Piouceau, L., Castagneyrol, B., Le Provost, G., Robin, S., Ritter, Y., Van Halder, I., Delzon, S., Bohan, D.A., Vacher, C., 2023b. Microbial biomarkers of tree water status for next‐generation biomonitoring of forest ecosystems. Molecular Ecology 32, 5944–5958. https://doi.org/10.1111/mec.17149
Fort, T., Pauvert, C., Chancerel, E., Burlett, R., Wingate, L., Vacher, C., 2023. Leaf microbiome data for European beech (Fagus sylvatica) at the leaf and canopy scales collected in a gallery forest in South-West France. Annals of Forest Science 80, 14. https://doi.org/10.1186/s13595-023-01181-z
Tamarelle, J., Penaud, B., Tyssandier, B., Guichoux, E., et al., 2023. Effects of azithromycin and doxycycline on the vaginal microbiota of women with urogenital Chlamydia trachomatis infection: a substudy of the Chlazidoxy randomized controlled trial. Clinical Microbiology and Infection 29, 1056–1062. https://doi.org/10.1016/j.cmi.2023.04.020
Ravigné, V., Becker, N., Massol, F., Guichoux, E., Boury, C., Mahé, F., Facon, B., 2022. Fruit fly phylogeny imprints bacterial gut microbiota. Evolutionary Applications n/a. https://doi.org/10.1111/eva.13352
Vacher, C., Francioni, C., Michel, M., Fort, T., Faivre d’Arcier, J., Chancerel, E., Delmotte, F., Delmas, C.E.L., 2022. Fungal Metabarcoding Data for Two Grapevine Varieties (Regent and Vitis vinifera ‘Cabernet-Sauvignon’) Inoculated with Powdery Mildew (Erysiphe necator) Under Drought Conditions. Phytobiomes Journal PBIOMES-06-22-0037-A. https://doi.org/10.1094/PBIOMES-06-22-0037-A
Aguayo J, Husson C, Chancerel E, Fabreguettes O, Chandelier A, Fourrier-Jeandel C, et al. Combining permanent aerobiological networks and molecular analyses for large-scale surveillance of forest fungal pathogens: A proof-of-concept. Plant Pathology. 2021;70(1):181‑94.https://doi.org/10.1111/ppa.13265
Enaud R, Cambos S, Viaud E, Guichoux E, Chancerel E, Marighetto A, et al. Gut Microbiota and Mycobiota Evolution Is Linked to Memory Improvement after Bariatric Surgery in Obese Patients: A Pilot Study. Nutrients. 13 nov 2021;13(11):4061. https://doi.org/10.3390/nu13114061